• 한국자기공명학회논문지
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• 제8권2호
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• pp.108-114
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• 2004

Recently a new method for magnetic resonance imaging based on the detection of relatively strong signal from intermolecular multiple quantum coherences (iMQCs) is reported. Such a signal would not be observable in the conventional framework of magnetic resonance; it originates in long-range dipolar couplings that are traditionally ignored. In this paper, we present the results of experimental studies to assess the feasibility of intermolecular double quantum coherences (iDQCs) imaging in humans. We show that the iDQC images are readily observable at 4T and that they do indeed provide different contrast than appears in conventional images.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.142-145
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• 2003

Many control applications using Neural Network need a priori information about the objective system. But it is impossible to get exact information about the objective system in real world. To solve this problem, several control methods were proposed. Reinforcement learning control using neural network is one of them. Basically reinforcement learning control doesn't need a priori information of objective system. This method uses reinforcement signal from interaction of objective system and environment and observable states of objective system as input data. But many methods take too much time to apply to real-world. So we focus on faster learning to apply reinforcement learning control to real-world. Two data types are used for reinforcement learning. One is reinforcement signal data. It has only two fixed scalar values that are assigned for each success and fail state. The other is observable state data. There are infinitive states in real-world system. So the number of observable state data is also infinitive. This requires too much learning time for applying to real-world. So we try to reduce the number of observable states by classification of states with Self-Organizing Map. We also use neural dynamic programming for controller design. An inverted pendulum on the cart system is simulated. Failure signal is used for reinforcement signal. The failure signal occurs when the pendulum angle or cart position deviate from the defined control range. The control objective is to maintain the balanced pole and centered cart. And four states that is, position and velocity of cart, angle and angular velocity of pole are used for state signal. Learning controller is composed of serial connection of Self-Organizing Map and two Multi-layer Feed-Forward Neural Networks.

• 논리연구
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• 제17권3호
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• pp.373-399
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• 2014

이 논문은 형이상학적 양진주의가 설득력 있는 견해인가에 대해서 비판적으로 논한다. 구체적으로 말해서 이 글은 "진리 대응설과 양진주의는 양립가능한가?", "관찰 가능한 모순이 존재하는가?" 즉 "경험세계가 비일관적일 수 있는가?" 그리고 "무모순율은 언어나 사고의 원리인가, 형이상학적 원리인가?"라는 세 가지 질문에 대해서 답함으로써 형이상학적 양진주의를 비판적으로 평가하는 것을 목적으로 한다. 결론적으로 진리 대응설과 양진주의가 양립가능하다고 가정하면 전진주의를 받아들이지 않을 수 없음을 보임으로써 진리 대응설과 양진주의가 양립 가능하지 않다고 논증하고, 무모순율을 세계를 제한하는 배제의 원리로 이해해야 함을 보이고, 이로부터 실재 세계는 일관된 세계이며, 모순은 실재하지 않음을 논증한다.

• Journal of Mechanical Science and Technology
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• 제19권6호
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• pp.1253-1267
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• 2005

Misalignment can be an important problem in the integration of GPS/INS. Observability analysis of the alignment errors in the integration of low-grade inertial sensors and multi-antenna GPS is presented in this paper. A control-theoretic approach is adopted to study the observability of time-varying error dynamics models. The relationship between vehicle motions and the observability of the errors in the lever arm and relative attitude between GPS antenna array and IMU is given. It is shown that alignment errors can be made observable through maneuvering. The change of acceleration makes the components of the relative attitude error that are orthogonal to the direction of the acceleration change observable. The change of angular velocity makes the components of the lever arm error that are orthogonal to the direction of the angular velocity observable. The motion of constant angular velocity has no influence on the estimation of the lever arm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2314-2333
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• 2023

It is significant to predict the performance degradation of complex electromechanical systems. Among the existing performance degradation prediction models, belief rule base (BRB) is a model that deal with quantitative data and qualitative information with uncertainty. However, when analyzing dynamic systems where observable indicators change frequently over time and working conditions, the traditional belief rule base (BRB) can not adapt to frequent changes in working conditions, such as the prediction of aeroengine performance degradation considering working condition. For the sake of settling this problem, this paper puts forward a new hidden belief rule base (HBRB) prediction method, in which the performance of aeroengines is regarded as hidden behavior, and operating conditions are used as observable indicators of the HBRB model to describe the hidden behavior to solve the problem of performance degradation prediction under different times and operating conditions. The performance degradation prediction case study of turbofan aeroengine simulation experiments proves the advantages of HBRB model, and the results testify the effectiveness and practicability of this method. Furthermore, it is compared with other advanced forecasting methods. The results testify this model can generate better predictions in aspects of accuracy and interpretability.

• 한국지형공간정보학회:학술대회논문집
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• 한국지형공간정보학회 1995년도 GPS, CNS, 지하매설물에 관한 워크샵
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• pp.21-32
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• 1995

• Journal of Mechanical Science and Technology
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• 제16권11호
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• pp.1367-1378
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• 2002

This paper investigates observability properties of strapdown INS aided by a GPS antenna array. The motivation to consider a GPS antenna array is that the lever-arms between the GPS antennas and IMU play an important role in the estimation of vehicle attitude and biases of IMU. It is shown that time-invariant INS error models are observable with measurements from at least three GPS antennas. It is also shown that time-varying error models are instantaneously observable with measurements from three antennas. Numerical simulation results are given to show the effectiveness of multiple GPS antennas on estimating vehicle attitude and biases of IMU when IMU has considerable magnitude of biases.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (2)
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• pp.343-345
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• 2004

최근 무선 기기 사용자가 급증하고 있다. 이에 따라 교통제어 시스템과 같은 모니터링 및 제어 응용이 무선 기기에서 활발히 사용될 것으로 예상된다. 본 논문에서는 모바일 응용 중 M/VC(Model/View Controller) 응용의 신속한 작성을 지원하는 모바일 M/VC 응용 프레임워크를 소개한다. 모바일 M/VC 응용 프레임워크는 무선 통신 환경에서 클라이언트와 서버 객체의 상호작용을 자동 처리하기 위해, Java의 관찰자/피관찰자(Observer/Observable)를 확장한 모바일 관찰자/피관찰자 패턴과 Multiplexer, Demultiplexer 클래스들을 지원한다. 개발자는 이 프레임워크를 이용하여 Observable과 MobileObserver 클래스들로부터 필요한 객체를 생성한 후, 이들을 Multiplexer와 Demultiplexer 클래스가 생성한 객체에 구성적으로 상호 연결하여 응용을 생성한다. 즉, 개발자는 무선 환경을 고려하지 않고 모바일 M/VC 응용 프레임워크가 제공하는 Multiplexer나 Demultiplexer 클래스의 객체에 무선 관찰자/피관찰자 객체들을 조립식으로 연결함으로써 피관찰자의 상태 변화가 관찰자에게 전달되고, 관찰자를 통한 사용자의 입력이 피관찰자에게 전달되어 반영되는 모바일 응용을 신속하게 생성할 수 있다. 따라서, 모바일 M/VC 응용 프레임워크는 무선 통신 환경하의 컴포넌트 재사용성을 개선하고, 모바일 M/VC 응용의 생산성을 향상시킨다.

• 제어로봇시스템학회논문지
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• 제10권7호
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• pp.575-582
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• 2004

The observer design problem is studied for a class of multi-output nonlinear systems that are not necessarily observable. Generalized nonlinear observer canonical form is introduced for multi-output nonlinear systems to design nonlinear observers. Sufficient conditions are given for a nonlinear system to be transformed by state-space change of coordinates into generalized nonlinear observer canonical form. Based on this canonical from, a sufficient condition is also given for the existence of nonlinear observers. An illustrative example is presented to show the design procedure of the proposed method.

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.365-369
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• 2009

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original ill-posed problem with a well-posed problem. The simulation and experimental results are presented and compared.